Administration of macrolide antibiotics increases cardiovascular risk.

Background: The increased risk of cardiovascular events in patients prescribed macrolides has been subject to debate for decades. Methods: Medline, EMBASE databases and ClinicalTrials.gov were searched from inception until August 31, 2022 for studies investigating the link between macrolides and cardiovascular risk. A meta-analysis was performed using a random-effects model. Results: A total of 80 studies involving 39,374,874 patients were included. No association was found between macrolides and all-cause death. However, compared with the non-macrolide group, macrolides were associated with a significantly increased risk of ventricular arrhythmia or sudden cardiac death (VA or SCD) (azithromycin, relative ratio [RR]: 1.53; 95% confidence interval [CI]: 1.19 to 1.97; clarithromycin, RR: 1.52; 95% CI: 1.07 to 2.16). Besides, administration of macrolides was associated with a higher risk of cardiovascular disease (CVD) death (azithromycin, RR: 1.63; 95% CI: 1.17 to 2.27) and a slightly increased risk of myocardial infarction (MI) (azithromycin, RR: 1.08; 95% CI: 1.02 to 1.15). Interestingly, no association was observed between roxithromycin and adverse cardiac outcomes. Increased risk of VA or SCD was observed for recent or current use of macrolides, MI for former use, and CVD death for current use. Conclusion: Administration of macrolide antibiotics and timing of macrolide use are associated with increased risk for SCD or VTA and cardiovascular death, but not all-cause death.

Characterization and pathogenicity of the porcine epidemic diarrhea virus isolated in China.

Piglet diarrhea caused by the porcine epidemic diarrhea virus (PEDV) is a common problem on pig farms in China associated with high morbidity and mortality rates. In this study, three PEDV isolates were successfully detected after the fourth blind passage in Vero cells. The samples were obtained from infected piglet farms in Jilin (Changchun), and Shandong (Qingdao) Provinces of China and were designated as CH/CC-1/2018, CH/CC-2/2018, and CH/QD/2018. According to the analysis of the complete S protein gene sequence, the CH/CC-1/2018 and CH/CC-2/2018 were allocated to the G2b branch, while CH/QD/2018 was located in the G1a interval and was closer to the vaccine strain CV777. Successful detection and identification of the isolated strains were carried out using electron microscopy and indirect immunofluorescence. Meanwhile, animal challenge experiments and viral RNA copies determination were used to compare the pathogenicity. The results showed that CH/CC-1/2018 in Changchun was more pathogenic than CH/QD/2018 in Qingdao. In conclusion, the discovery of these new strains is conducive to the development of vaccines to prevent the pandemic of PEDV, especially that the CH/CC-1/2018, and CH/CC-2/2018 were not related to the classical vaccine strain CV777.

Evaluating treatment strategies for non-small cell lung cancer during COVID-19: A propensity score matching analysis.

We employed pandemic treatment strategies that we developed at the beginning of the coronavirus disease 2019 (COVID-19) pandemic, and it was not clear whether any adverse results were associated with our strategies. Therefore, we carried out a retrospective study to compare our pandemic treatment strategies with prepandemic protocols to determine whether the strategies used during the high-risk period of COVID-19 were appropriate. The observation period was September 2019 to February 2020. Patients hospitalized from December 2019 to February 2020 were included as an experimental group, and individuals hospitalized from September 2019 to November 2019 were included as a control group. All non-small cell lung cancer patients hospitalized during the observation period were included except for pediatric and obstetric patients, patients younger than 18 years old, and patients admitted only for routine follow-up examinations. Treatment strategies were evaluated based on the prognosis of the different treatment methods, including surgical and nonsurgical treatments and discontinuation of therapy. Survival curves were analyzed using the Kaplan-Meier method. Cox regression analysis was used for multivariate analysis of risk factors for progress-free survival. Propensity score matching was used for clinical characteristics to adjust for selection bias. Therapy discontinuation in the experimental group was significantly higher than in the control group (P < .001). The differences in cancer progression and the number of deaths between the 2 groups were not significant (P = .38 and .13, respectively). For late-stage patients, there were significant differences in nonsurgical treatment and discontinued therapy (P < .001 and < .001, respectively) between the 2 groups, while the cancer progression and death toll differences were not significant (P = .20 and .20, respectively). For early-stage patients, the differences in surgical treatment, discontinued therapy, cancer progression, and death toll were not significant (P = .24, 0.24, 0.61, and 0.49, respectively) between the 2 groups. Multivariate analysis revealed that temporary discontinuation of therapy did not predict poor progress-free survival independently (hazard ratio = 1.007, 95% confidence interval: 0.653-1.552, P = .98). For patients in geographical regions with a high risk for COVID-19 infections, temporarily suspending treatment for late-stage non-small cell lung cancer patients is not likely to significantly impact their prognosis if they can return to treatment within 3 months of discontinuation.

Optimized Self-Adaptive Power Distribution for Microgrids in a Typical Tourism Water Village of Northern China under COVID-19 Background

This work presents an improved self-adaptive power distribution approach for the microgrid in five modes under different pandemic conditions in a typical tourism water village in Northern China. Differently from the other studies, this work concentrates on satisfying the specific power supply requirements under the COVID-19 background, with the maximum value of the composite index as the object function. Composite index includes not only the economic factors, but also some compulsive factors to ensure the requested power supply of the residents/tourists. The improved particle swarm optimization method which employs the modified weighted factor and the elite strategy is utilized to optimize the power dispatching of the microgrid. Moreover, the impact of the pandemic has been fully considered by comparing the power dispatching before and after the pandemic. The case study in Baiyangdian Region confirms the effectiveness of the proposed method. With this method, the optimal power dispatching is determined under different modes.

Peptide Binder with High-Affinity for the SARS-CoV-2 Spike Receptor-Binding Domain.

Rapid antigen detection tests are urgently needed for the early diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The discovery of a binder with high affinity and selectivity for the biomarkers presented by SARS-CoV-2 is crucial to the development of the rapid antigen detection method. We utilized the surface biopanning to identify a peptide binder R1 from a phage-displayed peptide library consisting of 109 independent phage recombinants. The R1 peptide exhibited high-affinity for specific binding with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with a dissociation constant KD of (7.5 ± 1.9) × 10-10 M, which maintained high binding affinity with the RBD derived from Gamma, Lambda, Delta, and Omicron variants. The composition and sequence dependence of binding characteristics in R1-RBD interactions was revealed by the binding affinity fluctuations between RBD and the scrambled sequences or single-site mutants of R1. The R1-functionalized gold nanoparticles possessed concentration-dependent response to RBD and selectivity over bovine serum albumin and human serum albumin. The peptide binder R1 shows the potential to be used for constructing a rapid detection method for the early-stage diagnostics for SARS-CoV-2.

Pathogenesis and Treatment of Cytokine Storm Induced by Infectious Diseases.

Cytokine storm is a phenomenon characterized by strong elevated circulating cytokines that most often occur after an overreactive immune system is activated by an acute systemic infection. A variety of cells participate in cytokine storm induction and progression, with profiles of cytokines released during cytokine storm varying from disease to disease. This review focuses on pathophysiological mechanisms underlying cytokine storm induction and progression induced by pathogenic invasive infectious diseases. Strategies for targeted treatment of various types of infection-induced cytokine storms are described from both host and pathogen perspectives. In summary, current studies indicate that cytokine storm-targeted therapies can effectively alleviate tissue damage while promoting the clearance of invading pathogens. Based on this premise, "multi-omics" immune system profiling should facilitate the development of more effective therapeutic strategies to alleviate cytokine storms caused by various diseases.

Synthetic Neutralizing Peptides Inhibit the Host Cell Binding of Spike Protein and Block Infection of SARS-CoV-2.

Antiviral treatments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been extensively pursued to conquer the pandemic. To inhibit the viral entry to the host cell, we designed and obtained three peptide sequences via quartz crystal microbalance measurement screening, which showed high affinity at nanomole to the S1 subunit of the spike protein and wild-type SARS-CoV-2 pseudovirus. Circular dichroism spectroscopy measurements revealed significant conformation changes of the S1 protein upon encounter with the three peptides. The peptides were able to effectively block the infection of a pseudovirus to 50% by inhibiting the host cell lines binding with the S1 protein, evidenced by the results from Western blotting and pseudovirus luciferase assay. Moreover, the combination of the three peptides could increase the inhibitory rate to 75%. In conclusion, the three chemically synthetic neutralizing peptides and their combinations hold promising potential as effective therapeutics in the prevention and treatment of COVID-19.

Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.

COVID-19 and pneumonia detection using medical images is a topic of immense interest in medical and healthcare research. Various advanced medical imaging and machine learning techniques have been presented to detect these respiratory disorders accurately. In this work, we have proposed a novel COVID-19 detection system using an exemplar and hybrid fused deep feature generator with X-ray images. The proposed Exemplar COVID-19FclNet9 comprises three basic steps: exemplar deep feature generation, iterative feature selection and classification. The novelty of this work is the feature extraction using three pre-trained convolutional neural networks (CNNs) in the presented feature extraction phase. The common aspects of these pre-trained CNNs are that they have three fully connected layers, and these networks are AlexNet, VGG16 and VGG19. The fully connected layer of these networks is used to generate deep features using an exemplar structure, and a nine-feature generation method is obtained. The loss values of these feature extractors are computed, and the best three extractors are selected. The features of the top three fully connected features are merged. An iterative selector is used to select the most informative features. The chosen features are classified using a support vector machine (SVM) classifier. The proposed COVID-19FclNet9 applied nine deep feature extraction methods by using three deep networks together. The most appropriate deep feature generation model selection and iterative feature selection have been employed to utilise their advantages together. By using these techniques, the image classification ability of the used three deep networks has been improved. The presented model is developed using four X-ray image corpora (DB1, DB2, DB3 and DB4) with two, three and four classes. The proposed Exemplar COVID-19FclNet9 achieved a classification accuracy of 97.60%, 89.96%, 98.84% and 99.64% using the SVM classifier with 10-fold cross-validation for four datasets, respectively. Our developed Exemplar COVID-19FclNet9 model has achieved high classification accuracy for all four databases and may be deployed for clinical application.

Clinical features and risk factors associated with severe COVID-19 patients in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world. In this study, we aimed to identify the risk factors for severe COVID-19 to improve treatment guidelines. METHODS: A multicenter, cross-sectional study was conducted on 313 patients hospitalized with COVID-19. Patients were classified into two groups based on disease severity (nonsevere and severe) according to initial clinical presentation. Laboratory test results and epidemiological and clinical characteristics were analyzed using descriptive statistics. Univariate and multivariate logistic regression models were used to detect potential risk factors associated with severe COVID-19. RESULTS: A total of 289 patients (197 nonsevere and 92 severe cases) with a median age of 45.0 (33.0, 61.0) years were included in this study, and 53.3% (154/289) were male. Fever (192/286, 67.1%) and cough (170/289, 58.8%) were commonly observed, followed by sore throat (49/289, 17.0%). Multivariate logistic regression analysis suggested that patients who were aged ≥ 65 years (OR: 2.725, 95% confidence interval [CI]: 1.317-5.636; P = 0.007), were male (OR: 1.878, 95% CI: 1.002-3.520, P = 0.049), had comorbid diabetes (OR: 3.314, 95% CI: 1.126-9.758, P = 0.030), cough (OR: 3.427, 95% CI: 1.752-6.706, P < 0.001), and/or diarrhea (OR: 2.629, 95% CI: 1.109-6.231, P = 0.028) on admission had a higher risk of severe disease. Moreover, stratification analysis indicated that male patients with diabetes were more likely to have severe COVID-19 (71.4% vs. 28.6%, χ2 = 8.183, P = 0.004). CONCLUSIONS: The clinical characteristics of those with severe and nonsevere COVID-19 were significantly different. The elderly, male patients with COVID-19, diabetes, and presenting with cough and/or diarrhea on admission may require close monitoring to prevent deterioration.

Comparison of patients hospitalized with COVID-19, H7N9 and H1N1.

BACKGROUND: There is an urgent need to better understand the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), for that the coronavirus disease 2019 (COVID-19) continues to cause considerable morbidity and mortality worldwide. This paper was to differentiate COVID-19 from other respiratory infectious diseases such as avian-origin influenza A (H7N9) and influenza A (H1N1) virus infections. METHODS: We included patients who had been hospitalized with laboratory-confirmed infection by SARS-CoV-2 (n = 83), H7N9 (n = 36), H1N1 (n = 44) viruses. Clinical presentation, chest CT features, and progression of patients were compared. We used the Logistic regression model to explore the possible risk factors. RESULTS: Both COVID-19 and H7N9 patients had a longer duration of hospitalization than H1N1 patients (P < 0.01), a higher complication rate, and more severe cases than H1N1 patients. H7N9 patients had higher hospitalization-fatality ratio than COVID-19 patients (P = 0.01). H7N9 patients had similar patterns of lymphopenia, neutrophilia, elevated alanine aminotransferase, C-reactive protein, lactate dehydrogenase, and those seen in H1N1 patients, which were all significantly different from patients with COVID-19 (P < 0.01). Either H7N9 or H1N1 patients had more obvious symptoms, like fever, fatigue, yellow sputum, and myalgia than COVID-19 patients (P < 0.01). The mean duration of viral shedding was 9.5 days for SARS-CoV-2 vs 9.9 days for H7N9 (P = 0.78). For severe cases, the meantime from illness onset to severity was 8.0 days for COVID-19 vs 5.2 days for H7N9 (P < 0.01), the comorbidity of chronic heart disease was more common in the COVID-19 patients than H7N9 (P = 0.02). Multivariate analysis showed that chronic heart disease was a possible risk factor (OR > 1) for COVID-19, compared with H1N1 and H7N9. CONCLUSIONS: The proportion of severe cases were higher for H7N9 and SARS-CoV-2 infections, compared with H1N1. The meantime from illness onset to severity was shorter for H7N9. Chronic heart disease was a possible risk factor for COVID-19.The comparison may provide the rationale for strategies of isolation and treatment of infected patients in the future.

Comparison of clinical characteristics between fecal/perianal swab nucleic acid-positive and -negative patients with COVID-19.

INTRODUCTION: We analyzed the clinical characteristics of COVID-19 fecal/perianal swab nucleic acid-positive patients in our hospital and evaluated the effect of SARS-CoV-2 on the gastrointestinal tract. METHODOLOGY: Ninety-seven patients in the Fifth Affiliated Hospital of Sun Yat-sen University from January 17, 2020 to March 2, 2020 with fecal/perianal swab samples were selected as subjects and the results of real-time fluorescence reverse transcriptase-PCR SARS-CoV-2 nucleic acid detection of fecal/perianal swabs were used to divide subjects into positive and negative groups. RESULTS: Fecal/perianal swabs of 53.61% (52/97) patients were positive including 31 males (59.62%) and 21 females (40.38%). The negative group had more females than males (P = 0.001). The distribution of case classification based on the most severe condition observed after admission was different between groups: five (5.15%) critical type patients were all from the positive group (P = 0.029). There was no statistical difference in clinical manifestations between the groups. In the positive group, the mean nucleic acid-negative conversion time was 14.13 ± 8.61 days, which was significantly later than the negative group (6.98 ± 5.16 days; P < 0.001). In the positive group, 92% (48/52) had nucleic acid-negative conversion with a mean nucleic acid-negative conversion time of 22.58 ± 10.30 days. Among them, 41 (78.85%) cases were delayed compared with pharynx/nasal swab nucleic acid-negative conversion time. CONCLUSIONS: The positive rate of fecal/perianal swab nucleic acid in male patients was higher than that in female patients. Fecal/perianal swab nucleic acid positive may be an indicator of critical conditions in those with COVID-19.

Relieving Cost of Epidemic by Parrondo's Paradox: A COVID-19 Case Study.

COVID-19, also known as SARS-CoV-2, is a coronavirus that is highly pathogenic and virulent. It spreads very quickly through close contact, and so in response to growing numbers of cases, many countries have imposed lockdown measures to slow its spread around the globe. The purpose of a lockdown is to reduce reproduction, that is, the number of people each confirmed case infects. Lockdown measures have worked to varying extents but they come with a massive price. Nearly every individual, community, business, and economy has been affected. In this paper, switching strategies that take into account the total "cost" borne by a community in response to COVID-19 are proposed. The proposed cost function takes into account the health and well-being of the population, as well as the economic impact due to the lockdown. The model allows for a comparative study to investigate the effectiveness of various COVID-19 suppression strategies. It reveals that both the strategy to implement a lockdown and the strategy to maintain an open community are individually losing in terms of the total "cost" per day. However, switching between these two strategies in a certain manner can paradoxically lead to a winning outcome-a phenomenon attributed to Parrondo's paradox.

Psychological status and behavior changes of the public during the COVID-19 epidemic in China.

BACKGROUND: A cluster of pneumonia cases were reported by Wuhan Municipal Health Commission, China in December 2019. A novel coronavirus was eventually identified, and became the COVID-19 epidemic that affected public health and life. We investigated the psychological status and behavior changes of the general public in China from January 30 to February 3, 2020. METHODS: Respondents were recruited via social media (WeChat) and completed an online questionnaire. We used the State-Trait Anxiety Inventory, Self-rating Depression Scale, and Symptom Checklist-90 to evaluate psychological status. We also investigated respondents' behavior changes. Quantitative data were analyzed by t-tests or analysis of variance, and classified data were analyzed with chi-square tests. RESULTS: In total, 608 valid questionnaires were obtained. More respondents had state anxiety than trait anxiety (15.8% vs 4.0%). Depression was found among 27.1% of respondents and 7.7% had psychological abnormalities. About 10.1% of respondents suffered from phobia. Our analysis of the relationship between subgroup characteristics and psychological status showed that age, gender, knowledge about COVID-19, degree of worry about epidemiological infection, and confidence about overcoming the outbreak significantly influenced psychological status. Around 93.3% of respondents avoided going to public places and almost all respondents reduced Spring Festival-related activities. At least 70.9% of respondents chose to take three or more preventive measures to avoid infection. The three most commonly used prevention measures were making fewer trips outside and avoiding contact (98.0%), wearing a mask (83.7%), and hand hygiene (82.4%). CONCLUSIONS: We need to pay more attention to public psychological stress, especially among young people, as they are likely to experience anxiety, depression, and psychological abnormalities. Different psychological interventions could be formulated according to the psychological characteristics of different gender and age groups. The majority of respondents followed specific behaviors required by the authorities, but it will take time to observe the effects of these behaviors on the epidemic.

Surface-Displayed Porcine IFN-λ3 in Lactobacillus plantarum Inhibits Porcine Enteric Coronavirus Infection of Porcine Intestinal Epithelial Cells.

Interferon (IFN)-λ plays an essential role in mucosal cells which exhibit strong antiviral activity. Lactobacillus plantarum (L. plantarum) has substantial application potential in the food and medical industries because of its probiotic properties. Alphacoronaviruses, especially porcine epidemic diarrhea virus (PEDV) and transmissible gastroenteritis virus (TGEV), cause high morbidity and mortality in piglets resulting in economic loss. Co-infection by these two viruses is becoming increasingly frequent. Therefore, it is particularly important to develop a new drug to prevent diarrhea infected with mixed viruses in piglets. In this study, we first constructed an anchored expression vector with CWA (C-terminal cell wall anchor) on L. plantarum. Second, we constructed two recombinant L. plantarum strains that anchored IFN-λ3 via pgsA (N-terminal transmembrane anchor) and CWA. Third, we demonstrated that both recombinant strains possess strong antiviral effects against coronavirus infection in the intestinal porcine epithelial cell line J2 (IPEC-J2). However, recombinant L. plantarum with the CWA anchor exhibited a more powerful antiviral effect than recombinant L. plantarum with pgsA. Consistent with this finding, Lb.plantarum-pSIP-409-IFN-λ3-CWA enhanced the expression levels of IFN-stimulated genes (ISGs) (ISG15, OASL, and Mx1) in IPEC-J2 cells more than did recombinant Lb.plantarum-pSIP-409-pgsA'-IFN-λ3. Our study verifies that recombinant L. plantarum inhibits PEDV and TGEV infection in IPEC-J2 cells, which may offer great potential for use as a novel oral antiviral agent in therapeutic applications for combating porcine epidemic diarrhea and transmissible gastroenteritis. This study is the first to show that recombinant L. plantarum suppresses PEDV and TGEV infection of IPEC-J2 cells.